scalation.minima

CheckLP

class CheckLP extends Error

This class checks the solution to Linear Programming (LP) problems. Given a constraint matrix 'a', limit/RHS vector 'b' and cost vector 'c', determine if the values for the solution/decision vector 'x' minimizes the objective function f(x), while satisfying all of the constraints, i.e.,

minimize f(x) = c x subject to a x <= b, x >= 0

Check the feasibility and optimality of the solution.

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Instance Constructors

  1. new CheckLP(a: MatrixD, b: VectorD, c: VectorD)

    a

    the M-by-N constraint matrix

    b

    the M-length limit/RHS vector (make b_i negative for ">=" constaint => surplus)

    c

    the N-length cost vector

Value Members

  1. final def !=(arg0: AnyRef): Boolean

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  2. final def !=(arg0: Any): Boolean

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  3. final def ##(): Int

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  7. def clone(): AnyRef

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  8. final def eq(arg0: AnyRef): Boolean

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  10. def finalize(): Unit

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  11. def flaw(method: String, message: String): Unit

    Show the flaw by printing the error message.

    Show the flaw by printing the error message.

    method

    the method where the error occurred

    message

    the error message

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  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. def isCorrect(x: VectorD, y: VectorD, f: Double): Boolean

    Check whether the solution is correct, feasible and optimal.

    Check whether the solution is correct, feasible and optimal.

    x

    the N-length primal solution vector

    y

    the M-length dual solution vector

    f

    the optimum (minimum) value of the objective function

  15. def isDualFeasible(y: VectorD): Boolean

    Is the solution dual feasible (y <= 0 and y a <= c)?

    Is the solution dual feasible (y <= 0 and y a <= c)?

    y

    the M-length dual solution vector

  16. final def isInstanceOf[T0]: Boolean

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  17. def isOptimal(x: VectorD, y: VectorD, f: Double): Boolean

    Check whether the optimum objective function value f == c x == y b.

    Check whether the optimum objective function value f == c x == y b.

    x

    the N-length primal solution vector

    y

    the M-length dual solution vector

    f

    the optimum (minimum) value of the objective function

  18. def isPrimalFeasible(x: VectorD): Boolean

    Is the solution primal feasible (x >= 0 and a x [<= | >=] b)?

    Is the solution primal feasible (x >= 0 and a x [<= | >=] b)?

    x

    the N-length primal solution vector

  19. final def ne(arg0: AnyRef): Boolean

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  20. final def notify(): Unit

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  22. final def synchronized[T0](arg0: ⇒ T0): T0

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  23. def toString(): String

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  24. final def wait(): Unit

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  25. final def wait(arg0: Long, arg1: Int): Unit

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  26. final def wait(arg0: Long): Unit

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